Predicting model of mild and severe types of COVID-19 patients using Thymus CT radiomics model: A preliminary study.

OBJECTIVE: To predict COVID-19 severity by building a prediction model based on the clinical manifestations and radiomic features of the thymus in COVID-19 patients. METHOD: We retrospectively analyzed the clinical and radiological data from 217 confirmed cases of COVID-19 admitted to Xiangyang NO.1 People's Hospital and Jiangsu Hospital of Chinese Medicine from December 2019 to April 2022 (including 118 mild cases and 99 severe cases). The data were split into the training and test sets at a 7:3 ratio. The cases in the training set were compared in terms of clinical data and radiomic parameters of the lasso regression model. Several models for severity prediction were established based on the clinical and radiomic features of the COVID-19 patients. The DeLong test and decision curve analysis (DCA) were used to compare the performances of several models. Finally, the prediction results were verified on the test set. RESULT: For the training set, the univariate analysis showed that BMI, diarrhea, thymic steatosis, anorexia, headache, findings on the chest CT scan, platelets, LDH, AST and radiomic features of the thymus were significantly different between the two groups of patients (P < 0.05). The combination model based on the clinical and radiomic features of COVID-19 patients had the highest predictive value for COVID-19 severity [AUC: 0.967 (OR 0.0115, 95%CI: 0.925-0.989)] vs. the clinical feature-based model [AUC: 0.772 (OR 0.0387, 95%CI: 0.697-0.836), P < 0.05], laboratory-based model [AUC: 0.687 (OR 0.0423, 95%CI: 0.608-0.760), P < 0.05] and model based on CT radiomics [AUC: 0.895 (OR 0.0261, 95%CI: 0.835-0.938), P < 0.05]. DCA also confirmed the high clinical net benefits of the combination model. The nomogram drawn based on the combination model could help differentiate between the mild and severe cases of COVID-19 at an early stage. The predictions from different models were verified on the test set. CONCLUSION: Severe cases of COVID-19 had a higher level of thymic involution. The thymic differentiation in radiomic features was related to disease progression. The combination model based on the radiomic features of the thymus could better promote early clinical intervention of COVID-19 and increase the cure rate.

Evaluation of thymic dimensions in patients with multisystem inflammatory syndrome.

BACKGROUND: Multisystem inflammatory syndrome (MIS-C) is the most important complication of COVID-19 in the pediatric population. Unfortunately, this problem is an unpredictable situation in patients with COVID-19. We aimed to evaluate the effects of MIS-C on thymus dimensions in pediatric patients. METHODS: We retrospectively analyzed the files of 368 pediatric patients aged 2-18 years, who were diagnosed with COVID-19. Computer Tomography (CT) images of 22 patients diagnosed with COVID-19 and 10 patients diagnosed with MIS-C were evaluated in detail by two board-certified radiologists. Eighteen age and sexmatched patients who applied to the emergency department of our hospital for any reason and had a CT scan for any reason were selected as the control group. The data of both groups were statistically compared. RESULTS: Considering the differences between the groups in terms of laboratory data, monocytes, hemoglobin, and platelet were significantly lower in the MIS-C group than the other groups. Procalcitonin, C- reactive protein, neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and proBNP levels were statistically significantly higher in the MIS-C group compared to the other groups Regarding the differences in thymus dimensions, thymus AP diameter, transverse diameter, length, thickness, and volume were significantly higher in the MIS-C group than in the other groups There was a significant positive correlation between the transverse diameter of the thymus and CRP, procalcitonin, pro-brain natriuretic peptide (proBNP), and NLR levels. CONCLUSIONS: Our study shows that thymus dimensions and acute phase reactants are higher in pediatric patients in the MIS-C group. Also, thymus transverse diameter, thymus thickness, and PLR values pose a risk for the development of MIS-C. More research is needed on the role of the thymus gland in the pathogenesis and diagnosis of MIS-C.

Influence of Covid-19 infection on fetal thymus size after recovery.

OBJECTIVES: To investigate the long-term effects of the SARS-CoV-2 infection on the fetal immune system by fetal thymus size measurements with ultrasound (USG). METHODS: This prospective study was conducted in the Turkish Ministry of Health Ankara City Hospital between November 1, 2020 and April 1, 2021, with recovered, pregnant women, four weeks after they had been confirmed for the SARS-CoV-2 infection by real-time polymerase-chain-reaction (RT-PCR). COVID-19 recovered (CR) pregnant women compared with age-matched pregnant controls in terms of demographic features, fetal thymic-thoracic ratio (TTR), and laboratory parameters. RESULTS: There was no difference in demographic features between the two groups. TTR found significantly lower in the CR group than the control group (p=0.001). The fetal TTR showed a significant and moderate correlation with maternal monocyte counts, monocyte to lymphocyte ratio (MLR), and red cell distribution width (RDW); while it did not correlate with lymphocyte counts, c-reactive protein (CRP), and procalcitonin levels. CONCLUSIONS: The 2019 novel coronavirus disease (COVID-19) reduces fetal thymus size in pregnant women with mild or moderate symptoms after recovery from the infection.

Evaluation of the chest computed tomography and hemogram data in patients with COVID-19: the importance of thymus

Background/aim: To investigate the relationship between imaging findings and peripheral blood cell counts of COVID-19 patients and the degree of thymus fat involution of these patients. Materials and methods: Computed tomography (CT) images of 87 patients with COVID-19 positive through RT-PCR testing were evaluated retrospectively by two radiologists. Ground glass densities and other signs of viral pneumonia were recorded, lung involvement was scored quantitatively. The patients thymus fat involution was graded on CT. Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratios (PLR), lymphocyte and platelet counts were calculated. Imaging findings and degrees of thymus fat involution were compared with laboratory data. Results: Quantitative scoring of lung involvement was calculated at mean 6.63 ± 4.70 (1­23) for observer 1 and mean 6.55 ± 4.65 (1­23) for observer 2 (K = 0.824­1.000). Statistical significance was determined between the increase in age and the increase in scores of lung findings (p = 0.003). Lymphocyte count (p = 0.0001) and PLR (p = 0.001) were significantly lower in patients with severe CT involvement. A statistically significantcorrelation was found between increased thymus fat component and presence of COVID-19 lung involvement in CT (r = 0.461). Conclusion: The severity of imaging findings for COVID-19 patients significantly correlates with the degree of fat involution in patients' thymus tissue.